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354 results about "Dynamic filtering" patented technology

Dynamic Filtering. Dynamic filtering is a way for you to choose a record from another sheet faster by filtering the sheet based on what you have entered on the sheet that you're entering. Similar to Ragic's cascaded selections, the list of records that you can choose can be based on what you entered on another field.

Methods, system and computer program products for dynamic filtering of network performance test results

Dynamic filtering methods, systems and computer program products are provided for network performance test results which may apply network troubleshooting expertise and knowledge of network topology to select and display test results in a manner which may facilitate analysis of those results by IT staffs. In a further aspect of the present invention, a severity index is provided which may be generated based on exception events from a plurality of network performance measurements, for example, response time, throughput and availability, which measurements are generated from test results obtained from agents located on various devices on a computer network. The test results may be obtained from either passive application monitor agents or active network test agents. In another aspect of the present invention, the exception events may be detected based on automatically generated threshold criteria which may be provided user selectable sensitivity and may be based on a specified percentage criteria relative to baseline performance results. In a further aspect of the present invention, the test results may be stored using data buckets with the number of data buckets and/or the range of each of the data buckets being selected to provide a desired overall range and granularity for each of the plurality of network performance measurement types. The range (width) of some of the data buckets may be narrower than others to provide greater resolution in a region of interest.
Owner:NETIQ

Method and system for registering and measuring leaks and flows

The present invention concerns a method of quantifying, detecting and localizing leaks or flows of liquid, gasses, or particles, in an oil or gas producing well (230). The method utilizes an acoustic transducer (150) arranged in the well (230). The method comprises steps of: (a) detecting signals (210) using the transducer (150), wherein the signals (210) are generated by acoustic noise from leaks (20) or flow of liquid, gasses, or particles in surroundings of the transducer (150); (b) amplifying the signals (210) to generate corresponding amplified signals for subsequent processing in a processing unit (170) disposed locally to the transducer (150); (c) filtering the amplified signals (210) over several frequency ranges using dynamic filtering for simultaneously detecting in these frequency ranges for better optimizing the signal-to-noise ratio by filtering away background noise in the amplified signals (210), and thereby generating corresponding processed data; and (d) sending the processed data from the processing unit (170) to a unit on the surface for storage and/or viewing of said data. The invention also comprises a corresponding system for implementing the method. The method and system are beneficially adapted for a continuous measurement up and/or down the oil or gas producing well. (230) in a non-stepwise manner.
Owner:ARCHER SA

Non-linear dynamic predictive device

A non-linear dynamic predictive device (60) is disclosed which operates either in a configuration mode or in one of three runtime modes: prediction mode, horizon mode, or reverse horizon mode. An external device controller (50) sets the mode and determines the data source and the frequency of data. In prediction mode, the input data are such as might be received from a distributed control system (DCS) (10) as found in a manufacturing process; the device controller ensures that a contiguous stream of data from the DCS is provided to the predictive device at a synchronous discrete base sample time. In prediction mode, the device controller operates the predictive device once per base sample time and receives the output from the predictive device through path (14). In horizon mode and reverse horizon mode, the device controller operates the predictive device additionally many times during base sample time interval. In horizon mode, additional data is provided through path (52). In reverse horizon mode data is passed in a reverse direction through the device, utilizing information stored during horizon mode, and returned to the device controller through path (66). In the forward modes, the data are passed to a series of preprocessing units (20) which convert each input variable (18) from engineering units to normalized units. Each preprocessing unit feeds a delay unit (22) that time-aligns the input to take into account dead time effects such as pipeline transport delay. The output of each delay unit is passed to a dynamic filter unit (24). Each dynamic filter unit internally utilizes one or more feedback paths that are essential for representing the dynamic information in the process. The filter units themselves are configured into loosely coupled subfilters which are automatically set up during the configuration mode and allow the capability of practical operator override of the automatic configuration settings. The outputs (28) of the dynamic filter units are passed to a non-linear analyzer (26) which outputs a value in normalized units. The output of the analyzer is passed to a post-processing unit (32) that converts the output to engineering units. This output represents a prediction of the output of the modeled process. In reverse horizon mode, a value of 1 is presented at the output of the predictive device and data is passed through the device in a reverse flow to produce a set of outputs (64) at the input of the predictive device. These are returned to the device controller through path (66). The purpose of the reverse horizon mode is to provide essential information for process control and optimization. The precise operation of the predictive device is configured by a set of parameters. that are determined during the configuration mode and stored in a storage device (30). The configuration mode makes use of one or more files of training data (48) collected from the DCS during standard operation of the process, or through structured plant testing. The predictive device is trained in four phases (40, 42, 44, and 46) correspo
Owner:ASPENTECH CORP

Preparation method for in situ self-assembled organic/inorganic hybrid membrane based on coordination

The invention provides a preparation method for an in situ self-assembled organic/inorganic hybrid membrane based on coordination, and belongs to the technical field of membrane separation. The method provided by the invention comprises the following steps: preprocessing the organic porous membrane and enabling the surface of which to be charged; preparing membrane casting solution by dissolving metal ion, organic ligand and polymer in a solution, and carrying out standing of the membrane casting solution for deaeration; conducting dynamic filtering or static deposition of the membrane casting solution on the surface of the organic porous membrane in an alternating manner for a period of time, so as to enable the metal ion and the organic ligand to generate hybrid particle on the surface of the membrane through the layer upon layer self-assembly method in the presence of polyelectrolyte, and forming an ultra-thin separation layer which is uniform in dispersity, high in loading capacity, and can realize molecular hybridization. The invention provides a novel preparation method for the organic/inorganic hybrid membrane, and nanofiltration membrane prepared by the method is provided with the advantages of high reject rate, big flux and the like, and the method can be widely used in the filed of water processing.
Owner:BEIJING UNIV OF TECH

Non-linear dynamic predictive device

A non-linear dynamic predictive device (60) is disclosed which operates either in a configuration mode or in one of three runtime modes: prediction mode, horizon mode, or reverse horizon mode. An external device controller (50) sets the mode and determines the data source and the frequency of data. In the forward modes (prediction and horizon), the data are passed to a series of preprocessing units (20) which convert each input variable (18) from engineering units to normalized units. Each preprocessing unit feeds a delay unit (22) that time-aligns the input to take into account dead time effects. The output of each delay unit is passed to a dynamic filter unit (24). Each dynamic filter unit internally utilizes one or more feedback paths that provide representations of the dynamic information in the process. The outputs (28) of the dynamic filter units are passed to a non-linear approximator (26) which outputs a value in normalized units. The output of the approximator is passed to a post-processing unit (32) that converts the output to engineering units. This output represents a prediction of the output of the modeled process. In reverse horizon mode, data is passed through the device in a reverse flow to produce a set of outputs (64) at the input of the predictive device. These are returned to the device controller through path (66). The purpose of the reverse horizon mode is to provide information for process control and optimization. The predictive device approximates a large class of non-linear dynamic processes. The structure of the predictive device allows it to be incorporated into a practical multivariable non-linear Model Predictive Control scheme, or used to estimate process properties.
Owner:ASPENTECH CORP

Dynamic filtering modeling downscaling method of environment variable on the basis of low-resolution satellite remote sensing data

The invention discloses a dynamic filtering modeling downscaling method of an environment variable on the basis of low-resolution satellite remote sensing data. The dynamic filtering modeling downscaling method comprises the following steps: firstly, carrying out aggregation calculation on 1km environment variable factors including eight pieces of data i.e., a vegetation index, a digital evaluation model, daytime surface temperature, night surface temperature, a topographic wetness index, a gradient, a slope aspect and a slope length gradient, into 25km to serve as independent variables, and taking corresponding 25Km resolution TRMM (Tropical Rainfall Measuring Mission) 3B43 v7 precipitation data as a dependent variable. An M5 method divides data sets formed by each environment variable into different vector spaces according to geographical similarity, then, the most effect environment variable is independently dynamically filtered in different vector spaces, and a divisional multiple regression model is independently established in the corresponding vector space; and the model is finally applied to the 1km environment variable to finally obtain a precipitation product of the 1km resolution. A downscaling result obtained by partitioning and dynamic factor filtering is obviously superior to a downscaling result based on a conventional regression model.
Owner:ZHEJIANG UNIV

Answer sheet identification method

The invention relates to an answer sheet identification method, which comprises the following steps: dynamically filtering and obtaining a colorful image of an answer sheet; carrying out gray processing to the image; judging whether a gray image is the processing of a "black" image; carrying out local threshold value binarization processing; looking up to process a convex quadrangle on a binary image, wherein the convex quadrangle has a maximum area and is more than a certain threshold value, and four inner corners of the convex quadrangle are similar to straight angles; carrying out inclination and perspective distortion correction processing; intercepting a rectangular area, and carrying out normalized image processing; identifying student numbers; identifying test paper numbers; and identifying answers. Due to the portability of a mobile terminal, a research that a mobile terminal camera is used for scanning an answer sheet and a relevant algorithm is used for identifying becomes very meaningful, the working efficiency of a teacher can be obviously improved, and the answer sheet identification method is helpful for teaching work. The answer sheet identification method also can be used for reference into the identification statistical processing of information cards, such as questionnaires, votes and the like, and has a wide application value.
Owner:BEIJING XUEXIN SUDA TECH

Spiral squeezing type sludge dewatering equipment

The invention discloses a spiral extrusion type sludge dewaterer comprising a frame (1), a water inlet part, an sludge outlet part (41), an water outlet part, a screw axis (2) and filter disc groups formed by the crossover interval arrangement of a plurality of annular static filter discs (5) and annular dynamic filter discs (6), wherein, each static filter disc (5) is fixed relatively to the frame (1), each dynamic filter disc (6) can form upper and lower spacing swinging movement relative to the frame (1) following the screw axis (2) under the driving of a transmission mechanism, and besides, the distance between the adjacent two static filter discs (5) is a little bigger than the thickness of the dynamic filter disc (6) so as to form a clearance (7) for water to flow through between the static filter discs (5) and dynamic filter discs (6). Compared with the prior art, the effluent water directly flows out from the clearances between filter disc groups, thus avoiding the abrasive action of sludge to the static filter discs and dynamic filter discs; and the device is long in service time, can realize solid-liquid separation by using only one power supply, and is low in energy consumption, and the parts is convenient to arrange, simple in structure and easy to practically implement.
Owner:浙江德安新技术发展有限公司
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